If I understand you can use replicate:
replicate(10, matmult(InitialPop, 1))
On Fri, Sep 11, 2009 at 1:11 PM, RFish <tomworthing...@talk21.com> wrote:
>
> Hi
>
> Sorry I don't seem to have explained what I'm trying to do very clearly.
> The piece of code below multiplies the two matrices together a number of
> times based on the value in the matmult(InitialPop,1) term in this case one
> (year), this gives me the end population for the analysis.
>
> InitialPop<-matrix(c(500,0,0,0,0,0,0))
>
> matmult<-function(InitialPop,N){
>
> mat3<-matrix(c(0,rnorm(1,0.6021,0.0987),0,0,0,0,0,0,0,rnorm(1,0.6021,0.0987),0,0,0,0,1.9,0,0,rnorm(1,0.6021,0.0987),0,0,0,4.8,0,0,0,rnorm(1,0.6021,0.0987),0,0,9.7,0,0,0,0,rnorm(1,0.6021,0.0987),0,18,0,0,0,0,0,rnorm(1,0.6021,0.0987),32.6,0,0,0,0,0,0),nrow=7)
>
> for (i in 1:N){
>
> PVAmatrix<-matrix(c(0,rnorm(1,0.6021,0.0987),0,0,0,0,0,0,0,rnorm(1,0.6021,0.0987),0,0,0,0,1.9,0,0,rnorm(1,0.6021,0.0987),0,0,0,4.8,0,0,0,rnorm(1,0.6021,0.0987),0,0,9.7,0,0,0,0,rnorm(1,0.6021,0.0987),0,18,0,0,0,0,0,rnorm(1,0.6021,0.0987),32.6,0,0,0,0,0,0),nrow=7)
> mat3<-mat3%*%PVAmatrix
> }
> ans<-mat3 %*% InitialPop
> return(ans)
> }
> matmult(InitialPop,1)
>
> The problem i have is to repeat this process say 1000 times and store this
> output in a format I can export easily whilst maintaining the randomness of
> the result, so that every end population is different.
>
> Any help would be brilliant
>
> Tom
>
>
>
>
>
>
> Chris Stubben wrote:
> >
> >
> > RFish wrote:
> >>
> >> I new to using R and am struggling with some matrix multiplication.
> >>
> >
> > I'm not sure what you're trying to print, but you could place this vector
> > in an expression
> >
> >
> mat3<-expression(c(0,rnorm(1,0.6021,0.0987),0,0,0,0,0,0,0,rnorm(1,0.6021,0.0987),0,0,0,0,1.9,0,0,rnorm(1,0.6021,0.0987),0,0,0,4.8,0,0,0,rnorm(1,0.6021,0.0987),0,0,9.7,0,0,0,0,rnorm(1,0.6021,0.0987),0,18,0,0,0,0,0,rnorm(1,0.6021,0.0987),32.6,0,0,0,0,0,0))
> >
> > # and then evaluate to get a new matrix each time
> > matrix(eval(mat3), nrow=7)
> >
> > #I think this may be easier to follow. First create a matrix of zeros,
> > stick in fertilities and then add random survival probabilities each time
> >
> >
> > mat3<-diag(0,7)
> > #fertilities
> > mat3[1,3:7]<-c(1.9, 4.8, 9.7, 18, 32.6)
> > # random survival on sub-diagonal
> > mat3[row(mat3)==col(mat3)+1]<-rnorm(6,0.6021,0.0987)
> >
> >
> > # and if you want to project the population over 10 time steps in a loop
> ?
> >
> > n<-matrix(c(500,0,0,0,0,0,0))
> >
> > popsize <- matrix(numeric(7 * 10), nrow = 7)
> > for (i in 1:10) {
> > popsize[, i] <- n
> > mat3[row(mat3)==col(mat3)+1]<-rnorm(6,0.6021,0.0987)
> > n <- mat3 %*% n
> > }
> >
> >
> > [,1] [,2] [,3] [,4] [,5] [,6] [,7]
> > [,8]
> > [1,] 500 0.0000 0.0000 531.6256 709.89940 940.19337 1697.52862
> > 3403.6610
> > [2,] 0 352.5116 0.0000 0.0000 298.97874 424.71160 561.32525
> > 1027.1605
> > [3,] 0 0.0000 279.8029 0.0000 0.00000 231.45988 316.83352
> > 424.8883
> > [4,] 0 0.0000 0.0000 147.8957 0.00000 0.00000 136.36804
> > 220.7370
> > [5,] 0 0.0000 0.0000 0.0000 96.92715 0.00000 0.00000
> > 108.6551
> > [6,] 0 0.0000 0.0000 0.0000 0.00000 69.87527 0.00000
> > 0.0000
> > [7,] 0 0.0000 0.0000 0.0000 0.00000 0.00000 65.86229
> > 0.0000
> >
> >
> > Chris Stubben
> >
> >
>
> --
> View this message in context:
> http://www.nabble.com/Matrix-multiplication-and-random-numbers-tp25365184p25403899.html
> Sent from the R help mailing list archive at Nabble.com.
>
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--
Henrique Dallazuanna
Curitiba-Paraná-Brasil
25° 25' 40" S 49° 16' 22" O
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